ashishkirtwed / Airfoil-self-noise-analysis-using-multivariate-Linear-Regression-in-python-

This repository is about using multivariate linear regression in airfoil self noise using python. It will help you to use different types of commands of different types of libraries in python.

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Airfoil-self-noise-analysis-using-multivariate-Linear-Regression-in-python-

The fundamental goal here is to model the sound pressure level as a function of the airfoil features and airspeed. DataSets Description 1. Frequency, in Hertzs, used as input 2. Angle_of_attack, in degrees, used as input. 3. Chord_length, in meters, used as input. 4. Free_stream_velocity, in meters per second, used as input. 5. Displacement thickness, in meters, used as input 6. scaled_sound_pressure_level, in decibels, used as the target. On the other hand, the NASA data set contains 1503 instances. They are divided at random into training and testing subsets, containing 75%, 25% of the instances, respectively. More specifically, 1127 samples are used here for training, 376 for testing. Once all the data set informationhas been set, we will perform some analytics to check the quality of the data.

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This repository is about using multivariate linear regression in airfoil self noise using python. It will help you to use different types of commands of different types of libraries in python.


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